Computer provisioning via API
Provision a sandboxed Linux machine through one API call, then use it as the computer for your agent’s desktop workflow.
Orgo
RevendiquerOrgo provides cloud computers for AI agents, with sandboxed Linux machines that boot fast and support browser, terminal, and file workflows.
Overview
Orgo is a developer platform for giving AI agents their own cloud computers. The service provisions sandboxed Linux machines with desktop, browser, terminal, and file access so agents can carry out computer-use workflows without running on a user’s personal machine.
The site positions Orgo for teams building and hosting agent fleets. It emphasizes fast boot times, isolated virtual machines, persistent files between sessions, and management through the dashboard, terminal, or API. Pricing is organized into Free, Developer, Startup, and Enterprise plans, with higher tiers adding more persistent computers, team features, and custom fleet options.
Features
Full desktop environment
The platform describes each machine as a full computer with apps, browser, terminal, and files, so agents can move between UI and code tasks.
Fast startup
Boots are described as under a second or sub-500ms, which is intended to reduce wait time when creating or replacing agent computers.
Persistent sessions and files
Keep computers online until you stop them and persist files between sessions, which supports longer-running workflows and stateful tasks.
Fleet management
Use the dashboard, terminal, or API to manage a fleet of computers rather than operating a single local machine.
Model and SDK compatibility
The source says Orgo works with Claude 4.8, GPT 5.5, Gemini 3.5, and custom models or loops, and supports Python or TypeScript SDKs.
Use Cases
Computer-use automation
Give an agent its own desktop when it needs to browse websites, interact with apps, or move between browser and terminal tasks in one workflow.
Agent fleet hosting
Run multiple agents on separate computers instead of sharing one local machine, which fits teams building production agent systems.
Persistent task workflows
Keep files and state available across sessions so an agent can continue a task after a restart or handoff.
Model-to-desktop integration
Connect a model you already use through the supported SDKs or custom loop when you want the model to operate a real computer rather than a narrow tool API.
Team and workspace operations
Create client-ready or isolated workspaces when you need team features, short-lived guest shares, or custom templates and golden images.
Pros and Cons
Pros
- Provisioning is described as fast, with computers booting in under a second or sub-500ms.
- Agents get a full computer environment, including apps, browser, terminal, and files.
- The platform supports persistence between sessions, which suits longer-running or stateful workflows.
- It works with multiple model and agent setups, including Claude Computer Use, OpenAI CUA, OpenClaw, Hermes Agent, and custom loops.
- Management options include the dashboard, terminal, API, and SDKs for Python and TypeScript.
Cons
- The source does not provide a detailed setup guide or documentation sample, so implementation depth is hard to judge from the page text alone.
- Some platform details, such as integrations and security controls beyond encryption and rotating credentials, are only partially documented in the collected sources.
FAQ
What is Orgo used for?
Orgo provides cloud computers for AI agents. The source describes creating a sandboxed Linux machine through the dashboard or API, then using it for browser work, code execution, file persistence, and computer-use workflows.
Which agents or SDKs does Orgo work with?
The source says Orgo supports Claude Computer Use, OpenAI’s CUA, OpenClaw, Hermes Agent, and custom loops. It also mentions Python and TypeScript SDKs for integrating a desktop your model can use.
How does Orgo handle security and isolation?
Orgo describes its computers as private, encrypted, and fully isolated virtual machines with rotating credentials and private sessions.
Does Orgo have paid plans?
The pricing page shows Free, Developer, Startup, and Enterprise plans, and the site also mentions dedicated capacity or an embedded runtime volume by contacting the team.
How quickly can a computer be created?
The source does not list a detailed setup guide, but it says a computer can be created in the dashboard in about fifteen seconds or provisioned through the API.
Quick Facts
- Category
- Developer Tool
- Primary use
- Cloud computers for AI agents
- Deployment model
- Sandboxed Linux virtual machines
- Access methods
- Dashboard, terminal, API
- Supported environments
- Apps, browser, terminal, files
- Plans mentioned
- Free, Developer, Startup, Enterprise